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algorithms in the simulation environment with grid use-case scenarios Integrate and validate solutions in the virtual grid environment. RT2: AI-driven state estimation and prediction This research aims
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investigate optimal control algorithms to control VFRMs using a VFRM and its driver prototypes. In addition to the experimental studies, a complete simulation framework will be developed, including both
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Validation of the developed algorithms in the simulation environment with grid use-case scenarios Integrate and validate solutions in the virtual grid environment. See for the other 3 reseach tracks below
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Master’s degrees (formal document if available, otherwise a self-declared document with the information). Electronic copy of (or a link to) Master thesis. Electronic copy of publications (if available
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and simulated on real distribution and transmission networks. Finally a system architecture will be developed that can be implemented in the control centers of the participating network operators and
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into requirements for designing and implementing the photonic integrated WSS and transmission systems. Design, simulate, and fabricate the photonic integrated MB-WSS and transmission systems based on the system
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are advantages. Excellent modeling skills in simulation tools such as PowerFactory or other equivalent open-source power system packages. Having experience in connecting such simulation tools with the programming
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integrated WSS and transmission systems. Design, simulate, and fabricate the photonic integrated MB-WSS and transmission systems based on the system specifications and network architecture. Packaging and
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of simulation-based solutions in the virtual grid environment See for the other 3 reseach tracks below: PhD1 / RT1: Synthetical data generation using multivariate models . PhD2 / RT2: AI-driven state estimation
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transcript of records for Bachelor’s and Master’s degrees. An electronic copy of (or a link to) Master thesis. An electronic copy of publications (if available; if more than 3, please submit top 3